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Agent skill

Atlas Map

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Map the system architecture — read the codebase, identify services and connections, output a C4-level architecture map as Mermaid diagrams with component descriptions.

MITAuto-check: notesDevelopment

Install Atlas Map

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill atlas-map -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace atlas-map --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ai-agency/tonone/skills/atlas-map .claude/skills/atlas-map && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
atlas-map
GitHub stars
2.8k
Token cost
~1.8k tokens
SKILL.md length
627 words
Files
2
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Map the system architecture — read the codebase, identify services and connections, output a C4-level architecture map as Mermaid diagrams with component descriptions.

  • Works in 7 steps: Read the Codebase → Identify the Pieces → Produce the C4 Level 1 — System Context → …
  • Asked to map the architecture
  • SKILL.md covers Operating Principle, Step 0: Read the Codebase, Step 1: Identify the Pieces and Step 2: Produce the C4 Level 1…, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Atlas Map is an agent skill from jeremylongshore/tons-of-skills-marketplace. Map the system architecture — read the codebase, identify services and connections, output a C4-level architecture map as Mermaid diagrams with component descriptions. Use when asked to "map the architecture", "system diagram", "how does this work", or "architecture overview".

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `.claude-plugin/plugin.json`).

It sits in Development. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Asked to map the architecture
  • How does this work
  • Architecture overview

Example prompts

  • “map the architecture”
  • “system diagram”
  • “how does this work”
  • “/atlas-map”

Requirements

  • Python 3
  • Docker
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Read the Codebase
  2. Identify the Pieces
  3. Produce the C4 Level 1 — System Context
  4. Produce the C4 Level 2 — Container Diagram
  5. Component Descriptions
  6. Observations
  7. Save

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash
    • Glob
    • Grep
    • WebFetch
    • WebSearch
    • Task
    • TodoWrite

    …and 1 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are mermaid).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Atlas Map loads about 1.8k tokens when it runs. Until then it costs about 72 tokens; SKILL.md has 627 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~72
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 627 words, ~1,780 tokens.

Download SKILL.mdSave it as .claude/skills/atlas-map/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
atlas-map
description
Map the system architecture — read the codebase, identify services and connections, output a C4-level architecture map as Mermaid diagrams with component descriptions. Use when asked to "map the architecture", "system diagram", "how does this work", or "architecture overview".
allowed-tools
Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion
version
0.6.4
author
tonone-ai <hello@tonone.ai>
license
MIT

Map the System Architecture

You are Atlas — the knowledge engineer from the Engineering Team. Produce an actual architecture map — not a template for making one. Read the codebase, understand the system, write the diagrams and descriptions.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Operating Principle

The map must answer one question clearly: How is this system structured and how do the pieces talk to each other? If someone reads it and still doesn't know where a request goes when it hits the system, the map has failed.

Use the C4 model as your abstraction framework. Level 1 (System Context) orients any audience. Level 2 (Container) orients a developer joining the team. Only go to Level 3 (Component) if a single service is complex enough to warrant it.

One diagram = one question. Split rather than pile on.

Step 0: Read the Codebase

Scan for structure indicators before writing anything:

  • Entry points: main.go, index.ts, app.py, server.*, cmd/
  • Package files: package.json, go.mod, pyproject.toml, Cargo.toml — frameworks and external deps
  • Services: docker-compose.yml, Dockerfile, services/, apps/, packages/ — deployable boundaries
  • Infrastructure: terraform/, pulumi/, cdk/, k8s/, helm/ — how it runs
  • CI/CD: .github/workflows/, Jenkinsfile — deploy targets and environments
  • Data: migration files, ORM configs, connection strings — what stores are in use
  • Existing docs: docs/architecture/, existing ADRs, README — don't duplicate what's already accurate

If the project is small enough that a single README paragraph describes the whole system, say so and produce a simpler map. Don't use C4 ceremony for a two-file script.

Step 1: Identify the Pieces

For each service, container, or significant module, determine:

  • What it does — one sentence, no jargon
  • What it talks to — other services, data stores, external APIs, queues
  • How it communicates — HTTP/REST, gRPC, message queue, SQL, direct import
  • What data it owns — which store, what schema (high level)
  • Where it runs — container, Lambda, Edge, mobile, browser

Identify external actors: human users (who?), external systems (what SaaS, what APIs), automated systems (cron, webhooks).

Step 2: Produce the C4 Level 1 — System Context

This diagram answers: What is this system, who uses it, and what external systems does it depend on or serve?

Write it as a Mermaid diagram. Use real names from the codebase — not placeholders.

mermaid
graph TB
    actor1["👤 [User type — e.g., 'End User']"]
    actor2["🤖 [Admin / Operator]"]

    subgraph system["[System Name]"]
        core["[Core System]"]
    end

    ext1["[External Service — e.g., Stripe]"]
    ext2["[External Service — e.g., SendGrid]"]
    db1[("[ Primary Database]")]

    actor1 -->|"[action — e.g., 'HTTP/S']"| core
    actor2 -->|"[action]"| core
    core -->|"[protocol]"| ext1
    core -->|"[protocol]"| ext2
    core -->|"SQL"| db1

Annotate each arrow with the communication type. "talks to" is not an annotation.

Show full SKILL.md (244 more words)Show less

Step 3: Produce the C4 Level 2 — Container Diagram

This diagram answers: What are the deployable units inside the system and how do they connect?

Only include containers that actually exist in the codebase. Don't invent microservices that aren't there.

mermaid
graph TB
    user["👤 User"]

    subgraph system["[System Name]"]
        web["[Web App]\n[React / Next.js]\nPort 3000"]
        api["[API Server]\n[Go / Gin]\nPort 8080"]
        worker["[Background Worker]\n[Python / Celery]"]
        db[("[ PostgreSQL\nUsers, Orders")]
        cache[("⚡ Redis\nSession, Rate limit")]
        queue["📨 [Queue — SQS / RabbitMQ]"]
    end

    stripe["💳 Stripe API"]
    email["📧 SendGrid"]

    user -->|"HTTPS"| web
    web -->|"REST/JSON"| api
    api -->|"SQL"| db
    api -->|"GET/SET"| cache
    api -->|"Publish"| queue
    queue -->|"Subscribe"| worker
    worker -->|"REST"| stripe
    worker -->|"REST"| email

Label each container with: name, technology stack, and what it owns. Keep labels concise.

Step 4: Component Descriptions

After the diagrams, write a short description for each container/service:

### [Service Name]
- **Purpose:** [one sentence]
- **Technology:** [language, framework, runtime]
- **Owns:** [data or functionality it's responsible for]
- **Connects to:** [what it depends on and how]
- **Runs on:** [Cloud Run, Lambda, EC2, Vercel, mobile, etc.]

Keep each description to 5 lines max. If it needs more, the service is probably doing too much — note that.

Step 5: Observations

After the diagrams and descriptions, write 2–5 observations about the architecture. Not a list of problems — observations about structure, coupling, failure modes, and scalability characteristics. Flag anything that should inform future decisions:

  • Single points of failure
  • Tight coupling between services that should be independent
  • Data ownership ambiguities (two services writing to the same table)
  • Missing resilience (no retry, no queue, synchronous chain of 4 services)
  • Surprising complexity for the system's current scale

Step 6: Save

Save to the project's existing docs location, or create it:

  • docs/architecture/system-context.md — Level 1 diagram + context
  • docs/architecture/containers.md — Level 2 diagram + component descriptions

If a docs/architecture/ directory already exists with accurate content, update it rather than duplicate.

Output Summary (CLI)

┌─ Architecture Map ──────────────────────────────────────┐
│ System: [name]                                          │
│ Containers: [N]  Data stores: [N]  External deps: [N]  │
├─────────────────────────────────────────────────────────┤
│ Diagrams                                                │
│   docs/architecture/system-context.md  (C4 Level 1)    │
│   docs/architecture/containers.md      (C4 Level 2)    │
├─────────────────────────────────────────────────────────┤
│ Observations                                            │
│   [!] [observation — e.g., single point of failure]    │
│   [i] [observation — e.g., auth service owns 3 DBs]    │
└─────────────────────────────────────────────────────────┘

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in plugins/ai-agency/tonone/skills/atlas-map of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • .claude-plugin/plugin.json

Open the folder on GitHubat commit cfae287

Compare with similar skills

Atlas Map next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Simple Englishmoeru-ai/airi50k2 repos~4.6kAutomated safety check: PassMIT
Mole CLI Release Flowtw93/Mole70k—~2.6kAutomated safety check: PassGPL-3.0
Babysit PR To Pass CIsgl-project/sglang37k2 repos~3kAutomated safety check: PassApache-2.0
Ansible Development Contextansible/ansible71k—~427Automated safety check: PassGPL-3.0

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Categories

Questions about Atlas Map

What does Atlas Map do?

Map the system architecture — read the codebase, identify services and connections, output a C4-level architecture map as Mermaid diagrams with component descriptions. Atlas Map is an agent skill from jeremylongshore/tons-of-skills-marketplace. Map the system architecture — read the codebase, identify services and connections, output a C4-level architecture map as Mermaid diagrams with component descriptions.

When should I use Atlas Map?

Atlas Map fits situations like: asked to map the architecture; how does this work; architecture overview.

How do I install Atlas Map in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill atlas-map -a claude-code`. Or copy the skill folder (plugins/ai-agency/tonone/skills/atlas-map in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/atlas-map in your project. Claude Code loads it when a task matches its description.

How do I install Atlas Map in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill atlas-map -a codex`. Or copy the skill folder (plugins/ai-agency/tonone/skills/atlas-map in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/atlas-map in your project. Codex loads it when a task matches its description.

Can I use Atlas Map in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill atlas-map -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/atlas-map, .gemini/skills/atlas-map, .github/skills/atlas-map and .opencode/skills/atlas-map in your project.

What does Atlas Map need to run?

SKILL.md names no scripts, command-line tools or credentials: Atlas Map is instructions for the agent only. Our summary lists: Python 3; Docker. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch, Task, TodoWrite, AskUserQuestion.

Does Atlas Map access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Atlas Map safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Atlas Map use?

Atlas Map is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Atlas Map use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Atlas Map?

Skills that share tags, products or a category with Atlas Map: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Simple English (moeru-ai/airi, 50k stars), Mole CLI Release Flow (tw93/Mole, 70k stars) and Babysit PR To Pass CI (sgl-project/sglang, 37k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Atlas Map?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.